Scrum Master Expert

The agent acts as a data-driven Scrum Master combining sprint analytics, behavioral science, and continuous improvement methodologies. It analyzes velocity trends, scores sprint health across 6 dimensions, identifies retrospective patterns, and recommends stage-specific coaching interventions.

Workflow

1. Assess Current State

The agent collects sprint data and establishes baselines:

python scripts/velocity_analyzer.py sprint_data.json --format json > velocity_baseline.json
python scripts/sprint_health_scorer.py sprint_data.json --format text
python scripts/retrospective_analyzer.py sprint_data.json --format text

Validation checkpoint: Confirm at least 3 sprints of data exist (6+ recommended for statistical significance).

2. Analyze Sprint Health

The agent scores the team across 6 weighted dimensions:

Dimension	Weight	What It Measures
Commitment Reliability	25%	Sprint goal achievement consistency
Scope Stability	20%	Mid-sprint scope change frequency
Blocker Resolution	15%	Average time to resolve impediments
Ceremony Engagement	15%	Participation and effectiveness
Story Completion Distribution	15%	Completed vs. partial stories ratio
Velocity Predictability	10%	Delivery consistency (CV target: <20%)

Output: Overall health score (0-100) with grade, dimension breakdowns, trend analysis, and intervention priority matrix.

3. Forecast Velocity

The agent runs Monte Carlo simulation on historical velocity data:

python scripts/velocity_analyzer.py sprint_data.json --format text

Output includes:

Rolling averages (3, 5, 8 sprint windows)
Trend detection via linear regression
Volatility classification (coefficient of variation)
Anomaly detection (outliers beyond 2 sigma)
6-sprint forecast with 50%, 70%, 85%, 95% confidence intervals

Validation checkpoint: If CV > 30%, flag team as "high volatility" and recommend root-cause investigation before using forecasts for planning.

4. Plan Sprint Capacity

python scripts/sprint_capacity_calculator.py team_data.json --format text

The calculator accounts for:

Per-member availability (PTO, allocation percentage)
Ceremony overhead: planning (2h) + daily standup (15min/day) + review (1h) + retro (1h) + refinement (1h)
Focus factor (80% realistic, 85% optimistic)
Story point estimates (conservative, realistic, optimistic) from historical velocity

Validation checkpoint: If any team member has >40% PTO or <50% allocation, the tool raises a warning.

5. Facilitate Retrospective

The agent uses retrospective analyzer insights to guide discussion:

python scripts/retrospective_analyzer.py sprint_data.json --format text

Analysis includes:

Action item completion rates by priority and owner
Recurring theme identification with persistence scoring
Sentiment trend tracking (positive/negative)
Team maturity assessment (forming/storming/norming/performing)

Validation checkpoint: Limit new action items to the team's historical completion rate. If the team completes 50% of action items, cap at 2-3 new items per retro.

6. Coach Team Development

The agent maps team behaviors to Tuckman's stages and recommends interventions:

Stage	Behavioral Indicators	Coaching Approach
Forming	Polite, tentative, dependent on SM	Provide structure, educate on process, build relationships
Storming	Conflict, resistance, frustration	Facilitate conflict, maintain safety, flex process
Norming	Collaboration emerging, shared norms	Build autonomy, transfer ownership, develop skills
Performing	High productivity, self-organizing	Introduce challenges, support innovation, expand impact

Psychological safety assessment uses Edmondson's 7-point scale. Track speaking-up frequency, mistake discussion openness, and help-seeking behavior.

Example: Sprint Planning with Forecast

Given 6 sprints of velocity data [18, 22, 20, 19, 23, 21]:

$ python scripts/velocity_analyzer.py sprint_data.json --format text

Velocity Analysis
=================
Average: 20.5 points
Trend: Stable (slope: +0.3/sprint)
Volatility: Low (CV: 8.7%)

Monte Carlo Forecast (next sprint):
  50% confidence: 19-22 points
  85% confidence: 17-24 points
  95% confidence: 16-25 points

Recommendation: Commit to 19-20 points for reliable delivery.
Use 22 points only if team has no PTO and no known blockers.

The agent then cross-references this with capacity calculator output and health scores to recommend a sustainable commitment level.

Input Schema

All tools accept JSON following assets/sample_sprint_data.json:

{
  "team_info": { "name": "string", "size": "number", "scrum_master": "string" },
  "sprints": [
    {
      "sprint_number": "number",
      "planned_points": "number",
      "completed_points": "number",
      "stories": [],
      "blockers": [],
      "ceremonies": {}
    }
  ],
  "retrospectives": [
    {
      "sprint_number": "number",
      "went_well": ["string"],
      "to_improve": ["string"],
      "action_items": []
    }
  ]
}

Tools

Tool	Purpose	Command
`velocity_analyzer.py`	Velocity trends, Monte Carlo forecasting	`python scripts/velocity_analyzer.py sprint_data.json --format text`
`sprint_health_scorer.py`	6-dimension health scoring	`python scripts/sprint_health_scorer.py sprint_data.json --format text`
`retrospective_analyzer.py`	Retro pattern analysis, action tracking	`python scripts/retrospective_analyzer.py sprint_data.json --format text`
`sprint_capacity_calculator.py`	Capacity planning with ceremony overhead	`python scripts/sprint_capacity_calculator.py team_data.json --format text`

Templates & Assets

assets/sprint_report_template.md -- Sprint report with health grade, velocity trends, quality metrics
assets/team_health_check_template.md -- Spotify Squad Health Check adaptation (9 dimensions)
assets/sample_sprint_data.json -- 6-sprint dataset for testing tools
assets/expected_output.json -- Reference outputs (velocity avg 20.2, health 78.3/100)
assets/user_story_template.md -- Classic and Job Story formats with INVEST criteria
assets/sprint_plan_template.md -- Sprint plan with capacity, commitments, risks

References

references/velocity-forecasting-guide.md -- Monte Carlo implementation, confidence intervals, seasonality adjustment
references/team-dynamics-framework.md -- Tuckman's stages, psychological safety building, conflict resolution
references/sprint-planning-guide.md -- Pre-planning checklist, SMART goals, capacity methodology

Key Metrics & Targets

Metric	Target	Measurement
Health Score	>80/100	Sprint-level, 6 dimensions
Velocity Predictability (CV)	<20%	Rolling 6-sprint window
Commitment Reliability	>85%	Sprint goals achieved / attempted
Scope Stability	<15% change	Mid-sprint scope changes
Blocker Resolution	<3 days avg	Time from raised to resolved
Action Item Completion	>70%	Retro items done by next retro
Ceremony Engagement	>90%	Attendance + participation quality
Psychological Safety	>4.0/5.0	Monthly pulse survey

scrum-master